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Reading-Network in Developmental Dyslexia Before and After Visual Training S S symmetry Article Reading-Network in Developmental Dyslexia before and after Visual Training Tihomir Taskov and Juliana Dushanova * Institute of Neurobiology, Bulgarian Academy of Sciences 1, 1113 Sofia, Bulgaria; [email protected] * Correspondence: [email protected]; Tel.: +35-(92)-979-3778 Received: 2 October 2020; Accepted: 29 October 2020; Published: 6 November 2020 Abstract: Electroencephalographic studies using graph-theoretic analysis have found aberrations in functional connectivity in dyslexics. How visual nonverbal training (VT) can change the functional connectivity of the reading network in developmental dyslexia is still unclear. We studied differences in the local and global topological properties of functional reading networks between controls and dyslexic children before and after VT. The minimum spanning tree method was used to construct the reading networks in multiple electroencephalogram (EEG) frequency bands. Compared to controls, pre-training dyslexics had a higher leaf fraction, tree hierarchy, kappa, and smaller diameter (θ—γ-frequency bands), and therefore, they had a less segregated neural network than controls. After training, the reading-network metrics of dyslexics became similar to controls. In β1 and γ-frequency bands, pre-training dyslexics exhibited a reduced degree and betweenness centrality of hubs in superior, middle, and inferior frontal areas in both brain hemispheres compared to the controls. Dyslexics relied on the left anterior temporal (β1, γ1) and dorsolateral prefrontal cortex (γ1), while in the right hemisphere, they relied on the occipitotemporal, parietal, (β1), motor (β2, γ1), and somatosensory cortices (γ1). After training, hubs appeared in both hemispheres at the middle occipital (β), parietal (β1), somatosensory (γ1), and dorsolateral prefrontal cortices (γ2), while in the left hemisphere, they appeared at the middle temporal, motor (β1), intermediate (γ2), and inferior frontal cortices (γ1, β2). Language-related brain regions were more active after visual training. They contribute to an understanding of lexical and sublexical representation. The same role has areas important for articulatory processes of reading. Keywords: EEG; functional connectivity; developmental dyslexia; frequency oscillations; reading of single words; visual training tasks; post-training network 1. Introduction Reading is a multifaceted process that is supported by sublexical and lexical routes [1]. The sublexical route performs the transformation between graphemes and phonemes, which is used when reading unfamiliar words [2]. The lexical path is indispensable when reading incorrect words, favors the reading of regular words, and does not contribute to the reading of pseudo-words [2]. Skillful reading relies on the lexical route, which supports rapid recognition of the orthographic word form of familiar words [3]. The brain applies these two reading strategies along two different neuronal pathways: dorsal (occipitoparietal sublexical) and ventral (occipitotemporal lexical) routes [1]. When reading aloud, in contrast to silent comprehension tasks, children can rely on orthographic and phonological information and less on semantic information. Extracting words from memory is a major component in the production of language and articulation. The initial stages of learning to read are related to children with problems with orthographic code violations [2]. The children need to learn how letters or groups of letters (grapheme) are mapped to their respective phonemes. Training instructions begin with the explicit teaching of letter–sound or grapheme–phoneme rules. Symmetry 2020, 12, 1842; doi:10.3390/sym12111842 www.mdpi.com/journal/symmetry Symmetry 2020, 12, 1842 2 of 18 Then, children use these rules or associations to decode words they have heard but not seen before. This process of phonological decoding is the basis of reading comprehension [3]. After basic decoding skills acquirement, explicit teaching is being replaced by self-learning and begins to decode the words automatically [3]. Many children with dyslexia have poor phoneme awareness skills and problems with the process from the associative decoding network [4]. The phonological deficit, which implies a deficit in phonological awareness, followed by a visual deficit related to poor spelling due to poor coding of the position of letters (e.g., inversion of letters), and global noise, which suggests the overall inefficiency of processing due to noisy calculations [5], underlie developmental dyslexia. In them, it must be anticipated how correcting one component would change the reading efficiency of different types of words. The learning of reading has great interpersonal differences in vocabulary, phonology, and orthographic skills. Knowing the effectiveness of the reading network is useful for understanding reading difficulties. Considering the human brain as a complex network of neurons and neuronal populations and the connections between them can lead to the emergence of complex patterns of connectivity between functionally diverse components. The “functional” relationships can be studied through statistical relationships between different functional components [6]. Brain networks are often studied in terms of functional segregation and integration. Functional segregation reflects the ability of the brain to specify locally information about the process, i.e., within a brain region or interconnected group of adjacent areas, while functional integration is the ability to combine information from different brain areas [7]. Functional analysis is a useful mathematical tool, which describes the brain networks as a set of nodes and their connections. Brain network integration and segregation can be characterized by graphical measures. The brain has been shown to exhibit properties of the small world [6]. Small world networks combine high local connectivity with high global integration. The small-world model was used in the study of the topological reorganization of functional brain networks during normal brain development [8] when the brain networks shift from a random topology to a more segregated small-world topology. Recent studies show that brain networks contain areas with tightly interconnected hubs, which process information in segregated modules, while the most important nodes, hubs, play a role in integrating information into the network [9]. The topology of functional brain networks plays an important role in understanding the human brain, normal functioning, pathology, and development. The brain networks of developmental dyslexia (DD) at rest have been well studied using an electroencephalogram [10]. Electroencephalogram (EEG) graph studies of the functional neural network of developmental dyslexia during the performance of tasks are missing. Although developmental dyslexia has been thoroughly studied at the behavioral level, there is no consensus on its causes. Different behavioral studies of dyslexics have found various deficits in the sensitivity to a coherence motion perception [11], velocity discrimination [12,13], motion direction encoding [14,15], and contrast sensitivity to stimuli with low-/high-spatial frequency in external noise [16]. These deficits are selectively associated with low accuracy or with slow performance on reading sub-skills [17], problems with clearly seeing letters and their order, and the orienting and focusing of visual–spatial attention [16]. The deficits in the magnocellular pathway, established by the coherent motion perception, were associated with letter decoding disability. The magnocellular system is the visual input to the dorsal pathway that mediates motion perception and object localization [18], due to the projections to the visual motion-sensitive area and the posterior parietal cortex. For reading, the dorsal pathway has a major role in directing the visual attention and control of eye movements [15]. The effectiveness of intervention efforts has also been studied [19–22]. After visual magnocellular training, children with reading difficulties improved coherent motion detection, the saccadic eye movements, as well as reading accuracy and visual errors [23]. By detecting progressively faster movements in the coherent motion discrimination, the lexical decision and reading accuracy improved at the higher visual levels in the magnocellular system [20]. The phonological errors for dyslexic readers decreased after magnocellular intervention by figure–ground movement discrimination [23,24]. Symmetry 2020, 12, 1842 3 of 18 The reduction in phonological errors and visual timing deficits, the improvements in reading fluency, attention, phonological processing, and working memory are the result of improvement in the functioning levels of the dorsal stream. However, more research is needed to determine the neurophysiological causes of dyslexia. Some studies have focused on examining changes in the activity of specific brain regions [25], but recent research has shown that the causes of deficits may lie in a disrupted relationship between specific brain regions [9]. The question is whether the theory of functional analysis of developmental dyslexia can shed light on the neurophysiological reasons for the observed effectiveness of training with visual nonverbal tasks [17,19,23]. The hypothesis is that training with visual tasks in children with developmental dyslexia may lead to changes in their brain networks so that they are more similar to those in controls. The main questions were to determine (1) whether these changes
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